Ubuntu 11.04 was released in the last month. Here is my instruction to install Cuda 4.0 on Ubuntu 11.04 on my Thinkpad T410 (thanks to instructions from http://forums.nvidia.com/index.php?showtopic=198030)
1. Install dependencies
sudo apt-get install build-essential gcc-4.4 g++-4.4 libxi-dev libxmu-dev freeglut3-dev
2. And download and install
- CUDA Toolkit for Ubuntu Linux 10.10 (sudo sh ...)
- CUDA Tools SDK (sudo sh ...)
- GPU Computing SDK code samples (no sudo)
from the following links:
| LINUX | DOWNLOADS |
|---|---|
| Developer Drivers for Linux (270.41.19) | 32-bit 64-bit |
CUDA Toolkit
| documentation |
| CUDA Toolkit for Fedora 13 | 32-bit 64-bit |
| CUDA Toolkit for RedHat Enterprise Linux 6.0 | 64-bit |
| CUDA Toolkit for RedHat Enterprise Linux 5.5 | 32-bit 64-bit |
| CUDA Toolkit for RedHat Enterprise Linux 4.8 | 64-bit |
| CUDA Toolkit for Ubuntu Linux 10.10 | 32-bit 64-bit |
| CUDA Toolkit for OpenSUSE 11.2 | 32-bit 64-bit |
| CUDA Toolkit for SUSE Linux Enterprise Server 11 SP1 | 32-bit 64-bit |
| CUDA Tools SDK | 32-bit 64-bit |
| GPU Computing SDK code samples | download |
3. Download the Developer Drivers for Linux (270.41.19) from the above link. For driver installation, you need to
(1) remove the current nvidia packages you might have installed
sudo apt-get remove nvidia-common nvidia-current
(2) go to the text window via ctrl+alt+F2.
(3) stop X
sudo service gdm stop(4) remove the nouveau module
sudo apt-get --purge remove xserver-xorg-video-nouveau(5) stop gdm and restart X
sudo service gdm startRestart the system
(6) stop X
sudo service gdm stop(7) install driver
sudo sh devdriver_4.0_linux_32_270.41.19.run(7) restart X
sudo service gdm start4. Assuming you have accepted the default install location /usr/local/cuda, you should add the following in the .bashrc file of your home folder.
export CUDA_HOME="/usr/local/cuda"
export LD_LIBRARY_PATH="${LD_LIBRARY_PATH}:${CUDA_HOME}/lib64"
export PATH=${CUDA_HOME}/bin:${PATH}
run ldconfig as root for it to take effect:
source ~/.bashrcand
sudo ldconfig5. make nvcc use gcc/g++ version 4.4, for example, in home directory
mkdir gcc44
cd gcc4
ln -s /usr/bin/cpp-4.4 cpp
ln -s /usr/bin/gcc-4.4 gcc
ln -s /usr/bin/g++-4.4 g++
edit /usr/local/cuda/bin/nvcc.profile to look in the gcc44 directory (give it the full path)
compiler-bindir =/home/xxx/gcc44 6. run make in NVIDIA_GPU_Computing_SDK/C
cd ~/NVIDIA_GPU_Computing_SDK/C
make
7. verify CUDA 4.0 installation by running the deviceQuery sample in the NVIDIA_GPU_Computing_SDK/C
bin/linux/release/deviceQuerymy Thinkpad T410 shows
[deviceQuery] starting...
linux/release/deviceQuery Starting...
CUDA Device Query (Runtime API) version (CUDART static linking)
Found 1 CUDA Capable device(s)
Device 0: "NVS 3100M"
CUDA Driver Version / Runtime Version 4.0 / 4.0
CUDA Capability Major/Minor version number: 1.2
Total amount of global memory: 256 MBytes (268107776 bytes)
( 2) Multiprocessors x ( 8) CUDA Cores/MP: 16 CUDA Cores
GPU Clock Speed: 1.47 GHz
Memory Clock rate: 810.00 Mhz
Memory Bus Width: 64-bit
Max Texture Dimension Size (x,y,z) 1D=(8192), 2D=(65536,32768), 3D=(2048,2048,2048)
Max Layered Texture Size (dim) x layers 1D=(8192) x 512, 2D=(8192,8192) x 512
Total amount of constant memory: 65536 bytes
Total amount of shared memory per block: 16384 bytes
Total number of registers available per block: 16384
Warp size: 32
Maximum number of threads per block: 512
Maximum sizes of each dimension of a block: 512 x 512 x 64
Maximum sizes of each dimension of a grid: 65535 x 65535 x 1
Maximum memory pitch: 2147483647 bytes
Texture alignment: 256 bytes
Concurrent copy and execution: Yes with 1 copy engine(s)
Run time limit on kernels: Yes
Integrated GPU sharing Host Memory: No
Support host page-locked memory mapping: Yes
Concurrent kernel execution: No
Alignment requirement for Surfaces: Yes
Device has ECC support enabled: No
Device is using TCC driver mode: No
Device supports Unified Addressing (UVA): No
Device PCI Bus ID / PCI location ID: 1 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 4.0, CUDA Runtime Version = 4.0, NumDevs = 1, Device = NVS 3100M
[deviceQuery] test results...
PASSED
Press ENTER to exit...
linux/release/deviceQuery Starting...
CUDA Device Query (Runtime API) version (CUDART static linking)
Found 1 CUDA Capable device(s)
Device 0: "NVS 3100M"
CUDA Driver Version / Runtime Version 4.0 / 4.0
CUDA Capability Major/Minor version number: 1.2
Total amount of global memory: 256 MBytes (268107776 bytes)
( 2) Multiprocessors x ( 8) CUDA Cores/MP: 16 CUDA Cores
GPU Clock Speed:
Memory Clock rate:
Memory Bus Width:
Max Texture Dimension Size (x,y,z) 1D=(8192), 2D=(65536,32768), 3D=(2048,2048,2048)
Max Layered Texture Size (dim) x layers 1D=(8192) x 512, 2D=(8192,8192) x 512
Total amount of constant memory: 65536 bytes
Total amount of shared memory per block: 16384 bytes
Total number of registers available per block: 16384
Warp size:
Maximum number of threads per block: 512
Maximum sizes of each dimension of a block: 512 x 512 x 64
Maximum sizes of each dimension of a grid: 65535 x 65535 x 1
Maximum memory pitch:
Texture alignment:
Concurrent copy and execution: Yes with 1 copy engine(s)
Run time limit on kernels: Yes
Integrated GPU sharing Host Memory: No
Support host page-locked memory mapping: Yes
Concurrent kernel execution: No
Alignment requirement for Surfaces: Yes
Device has ECC support enabled: No
Device is using TCC driver mode: No
Device supports Unified Addressing (UVA): No
Device PCI Bus ID / PCI location ID: 1 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 4.0, CUDA Runtime Version = 4.0, NumDevs = 1, Device = NVS 3100M
[deviceQuery] test results...
PASSED
Press ENTER to exit...
22 comments:
Hi
I have some problems with your installation guide
compiler-bindir=/home/xxxx/gcc44
where should I add this in nvcc.profile?
but after installing my ubuntu don't boot in normal mode and has this log
API mismatch the nvidia kernel module has version 173.14.30 but this nvidia driver component has version 270.41.19
(I have G98[Geforce 9300 M GS])
I put
compiler-bindir =/home/xxx/gcc44
in the last line of /usr/local/cuda/bin/nvcc.profile
Did you run
sudo apt-get remove nvidia-common nvidia-current
to remove your previous driver. Ideally you should use the new installed driver just downloaded from
http://developer.nvidia.com/cuda-toolkit-40#Linux
Thanks very much for this. I had a little difficulty getting the dev driver to install (Ubuntu 11.04, Dell XPS M1530), but I kept plugging at it, and....
pcarroll@pcarroll-XPS-M1530:~/NVIDIA_GPU_Computing_SDK/C$ bin/linux/release/deviceQuery
[deviceQuery] starting...
bin/linux/release/deviceQuery Starting...
CUDA Device Query (Runtime API) version (CUDART static linking)
Found 1 CUDA Capable device(s)
Device 0: "GeForce 8600M GT"
CUDA Driver Version / Runtime Version 4.0 / 4.0
CUDA Capability Major/Minor version number: 1.1
Total amount of global memory: 256 MBytes (268107776 bytes)
( 4) Multiprocessors x ( 8) CUDA Cores/MP: 32 CUDA Cores
GPU Clock Speed: 0.95 GHz
Memory Clock rate: 702.00 Mhz
Memory Bus Width: 128-bit
Max Texture Dimension Size (x,y,z) 1D=(8192), 2D=(65536,32768), 3D=(2048,2048,2048)
Max Layered Texture Size (dim) x layers 1D=(8192) x 512, 2D=(8192,8192) x 512
Total amount of constant memory: 65536 bytes
Total amount of shared memory per block: 16384 bytes
Total number of registers available per block: 8192
Warp size: 32
Maximum number of threads per block: 512
Maximum sizes of each dimension of a block: 512 x 512 x 64
Maximum sizes of each dimension of a grid: 65535 x 65535 x 1
Maximum memory pitch: 2147483647 bytes
Texture alignment: 256 bytes
Concurrent copy and execution: Yes with 1 copy engine(s)
Run time limit on kernels: Yes
Integrated GPU sharing Host Memory: No
Support host page-locked memory mapping: Yes
Concurrent kernel execution: No
Alignment requirement for Surfaces: Yes
Device has ECC support enabled: No
Device is using TCC driver mode: No
Device supports Unified Addressing (UVA): No
Device PCI Bus ID / PCI location ID: 1 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 4.0, CUDA Runtime Version = 4.0, NumDevs = 1, Device = GeForce 8600M GT
[deviceQuery] test results...
PASSED
THANKS!!!!!
nice tutorial thanks.
I'm using the latast nvidia driver via ppa instead of the cuda dev driver (devdriver_4.0_linux_64_270.41.19.run).
$ sudo add-apt-repository ppa:ubuntu-x-swat/x-updates
$ sudo apt-get update
$ sudo apt-get upgrade # or sudo apt-get install nvidia-current
$ sudo reboot
No need to remove the nouveau driver etc.
In this case, however, you should do some workarounds to avoid bugs of SDK:
$ cd ~/NVIDIA_GPU_Computing_SDK/C
$ LPATH=/usr/lib64/nvidia-current make # in 32bit environment, use lib instead of lib64
thank you, good tutorial
Hi
I can not properly install nvidia driver to T410 with NVS 3100M. After creating xorg.conf by nvidia-xconfig X does not start with message 'fatal error, no screen found'
Could you help with that please.
thank you for your guidance install Cuda in my Ubuntu.
I used few posts and made bash script for installation.
http://pastebin.com/PyDnT2q6
Nvidia Cuda 4.0 on Ubuntu 11.04
Link to download:
pastebin.com/download.php?i=PyDnT2q6
1. save it like *.sh
2. give the permittions
sudo chmod +x
3. switch shell mode with CTRL+ALT+F1
4. execute script
I'm having an issue when I try to run make in NVIDIA_GPU_Computing_SDK/C.
I keep getting this error:
make[1]: Entering directory `/home/uvuphys/NVIDIA_GPU_Computting_SDK/C/common'
cc1plus: warning: command line option ‘-Wimplicit’ is valid for C/ObjC but not for C++ [enabled by default]
src/cutil.cpp:28:27: fatal error: builtin_types.h: No such file or directory
compilation terminated.
make[1]: *** [obj/i386/release/cutil.cpp.o] Error 1
make[1]: Leaving directory `/home/uvuphys/NVIDIA_GPU_Computting_SDK/C/common'
make: *** [lib/libcutil.so] Error 2
Any suggestions on what I could be doing wrong?
Thanks for your help.
This blog is truly awesome in all aspects.
cudo
I sent your articles links to all my contacts and they all love it including me.
how to get a phlebotomy certification
I conceive feeling to have the accumulation that you are card.
Go to Herbal Bath
You guys make it really easy for all the folks out there.
Healthy Relationship with Herbal Bath
I'm sure coming again to construe these articles and blogs Tips by VIP Kontor
Your way to enlighten everything on this blog is actually pleasant, everyone manage to efficiently be familiar with it, Thanks a great deal.
Learn More About RCM Software
These articles and blogs are truly enough for me for a day.
Get more info about Deco En Bois
I will prefer this blog because it has much more informative stuff.
Visit Economy Fence
I outright point of view and revalue your repair on every objective.
payday loans online direct lenders
Great webs site with mesmerizing and unique material what else you would like.
payday loan
It's offensively easy to seek out any matter on web as compared to books, as I found this text at this website. Relationship Issues With Hongen 88
Post a Comment